Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
A review on deep learning techniques applied to semantic segmentation
Image semantic segmentation is more and more being of interest for computer vision and
machine learning researchers. Many applications on the rise need accurate and efficient …
machine learning researchers. Many applications on the rise need accurate and efficient …
Brain tumor segmentation with deep neural networks
In this paper, we present a fully automatic brain tumor segmentation method based on Deep
Neural Networks (DNNs). The proposed networks are tailored to glioblastomas (both low …
Neural Networks (DNNs). The proposed networks are tailored to glioblastomas (both low …
A survey on deep learning techniques for image and video semantic segmentation
Image semantic segmentation is more and more being of interest for computer vision and
machine learning researchers. Many applications on the rise need accurate and efficient …
machine learning researchers. Many applications on the rise need accurate and efficient …
Computer vision for autonomous vehicles: Problems, datasets and state of the art
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
Hdmapnet: An online hd map construction and evaluation framework
Constructing HD semantic maps is a central component of autonomous driving. However,
traditional pipelines require a vast amount of human efforts and resources in annotating and …
traditional pipelines require a vast amount of human efforts and resources in annotating and …
A new performance measure and evaluation benchmark for road detection algorithms
Detecting the road area and ego-lane ahead of a vehicle is central to modern driver
assistance systems. While lane-detection on well-marked roads is already available in …
assistance systems. While lane-detection on well-marked roads is already available in …
Sne-roadseg: Incorporating surface normal information into semantic segmentation for accurate freespace detection
Freespace detection is an essential component of visual perception for self-driving cars. The
recent efforts made in data-fusion convolutional neural networks (CNNs) have significantly …
recent efforts made in data-fusion convolutional neural networks (CNNs) have significantly …
Automatic road detection and centerline extraction via cascaded end-to-end convolutional neural network
Accurate road detection and centerline extraction from very high resolution (VHR) remote
sensing imagery are of central importance in a wide range of applications. Due to the …
sensing imagery are of central importance in a wide range of applications. Due to the …
Crowded scene analysis: A survey
Automated scene analysis has been a topic of great interest in computer vision and
cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded …
cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded …